The Data Science and Machine Learning team at Fair is part of the Engineering organization and oversees risk, vehicle valuation, and personalization efforts. We usually run a few steps ahead of other engineering team and work with product leads frequently where DS techniques can be used to improve our product and customer experience.
You will report to the Data Science Manager and your role will involve the development of pipelines and backend services that host machine learning models for all projects. You will model application R&D and support backend engineering teams with service integrations and analytics teams for goal analysis.
- Work with other engineering and teams to help improve the shopping and ownership experience at Fair
- Brainstorm, scope and develop ideas that influence goals
- Design machine learning models, associated pipelines, explore new prediction algorithms, construct new features, and research new technologies
- Contribute to our distributed learning and deployment platform
- At least 3 years of experience as a Data Scientist/Machine learning engineer with a focus on building and deploying production facing ML and ETL pipelines
- Development experience in Python
- Experience with standard supervised (especially decision trees) and unsupervised learning methods, time series analysis and causal inference
- Development experience with scikit-learn, tensorflow/keras, XGBoost or LightGBM
- Bachelor’s degree in computer science or a quantitative discipline
- Experience with the following - Golang or Ruby, running multi-armed A/B tests, deep learning, NLP techniques and kaggle competitions
- 100% coverage of medical, dental and vision benefits for employees AND their families
- Equity incentives
- Unlimited vacation package
- Up to four months 100% paid parental leave
- Cell Phone reimbursement
- Employee referrals rewards
- Diverse and inclusive culture
It’s Fair’s policy to provide equal opportunity in employment to all employees and applicants for employment. No person will be discriminated against in employment because of race, color, religion, gender, gender expression, gender identity, sex, medical condition (as defined by California law and which includes pregnancy or childbirth), national origin, age, physical or mental disability, political activity or affiliation, ancestry, marital status, protected veteran status, citizenship status, sexual orientation, genetic information, taking or requesting statutorily protected leave, or any other legally protected status where there is no bona fide occupational qualification or legitimate business reason for the differing treatment. In addition, Fair prohibits harassment on any of the bases listed above or any other characteristics protected under federal, state or local laws.